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2021 Journal article Open Access OPEN

ReLock: a resilient two-phase locking RESTful transaction model
Frosini L., Pagano P., Candela L., Simi M., Bernardeschi C.
Service composition and supporting transactions across composed services are among the major challenges characterizing service-oriented computing. REpresentational State Transfer (REST) is one of the approaches used for implementing Web services that is gaining momentum thanks to its features making it suitable for cloud computing and microservices-based contexts. This paper introduces ReLock, a resilient RESTful transaction model introducing general purpose transactions on RESTful services by a layered approach and a two-phase locking mechanism not requesting any change to the RESTful services involved in a transaction.Source: Service-oriented computing and applications (Internet) (2021). doi:10.1007/s11761-020-00311-z
DOI: 10.1007/s11761-020-00311-z
Project(s): Blue Cloud via OpenAIRE

See at: ISTI Repository Open Access | Service Oriented Computing and Applications Restricted | link.springer.com Restricted | Service Oriented Computing and Applications Restricted | Service Oriented Computing and Applications Restricted | CNR ExploRA Restricted


2021 Report Open Access OPEN

ARIADNEPlus - VREs operation mid-term activity report
Assante M., Cirillo R., Dell'Amico A., Pagano P., Candela L., Frosini L., Lelii L., Mangiacrapa F., Panichi G., Sinibaldi F.
This deliverable D13.2 - "VREs Operation Mid-term Activity Report" describes the activities carried out during the first 24 months of the ARIADNEplus project within Work Package 13. Specifically, in Task 13.1 Infrastructure Operation (JRA2.1) and Task 13.3 VREs Operation (JRA2.3). It reports the procedures governing the operation of the VREs as well as the status of the aggregated resources at mid-term in the ARIADNEplus infrastructure.Source: Project report, ARIADNEplus, D13.2, 2021
Project(s): ARIADNEplus via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2021 Journal article Open Access OPEN

An Open Science approach to infer fishing activity pressure on stocks and biodiversity from vessel tracking data
Coro G., Ellenbroek A., Pagano P.
Vessel tracking data help study the potential impact of fisheries on biodiversity and produce risk assessments. Existing workflows process vessel tracks to identify fishing activity and integrate information on species vulnerability. However, there are significant data integration challenges across the data sources needed for an integrated impact assessment due to heterogeneous nomenclatures, data accessibility issues, geographical and computational scalability of the processes, and confidentiality and transparency towards decision making authorities. This paper presents an Open Science data integration approach to use vessel tracking data in integrated impact assessments. Our approach combines heterogeneous knowledge sources from fisheries, biodiversity, and environmental observations to infer fishing activity and risks to potentially impacted species. An Open Science e-Infrastructure facilitates access to data sources and maximises the reproducibility of the results and the method's reusability across several application domains. Our method's quality is assessed through three case studies: The first demonstrates cross-dataset consistency by comparing the results obtained from two different vessel data sources. The second performs a temporal pattern analysis of fishing activity and potentially impacted species over time. The third assesses the potential impact of reduced fishing pressure on marine biodiversity and threatened species due to the 2020 COVID-19 lockdown in Italy. The method is meant to be integrated with other systems through its Open Science-oriented features and can rapidly use new sources of findable, accessible, interoperable, and reusable (FAIR) data. Other systems can use it to (i) classify vessel activity in data-limited scenarios, (ii) identify bycatch species (when catchability data are available), and (iii) study the effects of fisheries on habitats and populations' growth.Source: Ecological informatics (Print) 64 (2021). doi:10.1016/j.ecoinf.2021.101384
DOI: 10.1016/j.ecoinf.2021.101384
Project(s): Blue Cloud via OpenAIRE

See at: ISTI Repository Open Access | ISTI Repository Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | www.sciencedirect.com Open Access


2020 Contribution to book Open Access OPEN

Data Processing and Analytics for Data-Centric Sciences
Candela L., Coro G., Lelii L., Panichi G., Pagano P.
The development of data processing and analytics tools is heavily driven by applications, which results in a great variety of software solutions, which often address specific needs. It is difficult to imagine a single solution that is universally suitable for all (or even most) application scenarios and contexts. This chapter describes the data analytics framework that has been designed and developed in the ENVRIplus project to be (a) suitable for serving the needs of researchers in several domains including environmental sciences, (b) open and extensible both with respect to the algorithms and methods it enables and the computing platforms it relies on to execute those algorithms and methods, and (c) open-science-friendly, i.e. it is capable of incorporating every algorithm and method integrated into the data processing framework as well as any computation resulting from the exploitation of integrated algorithms into a "research object" catering for citation, reproducibility, repeatability and provenance.Source: Towards Interoperable Research Infrastructures for Environmental and Earth Sciences. A Reference Model Guided Approach for Common Challenges., edited by Zhao Z.; Hellström M., pp. 176–191, 2020
DOI: 10.1007/978-3-030-52829-4_10
Project(s): ENVRI PLUS via OpenAIRE

See at: link.springer.com Open Access | link.springer.com Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | academic.microsoft.com Restricted | link.springer.com Restricted | link.springer.com Restricted | link.springer.com Restricted


2020 Journal article Open Access OPEN

NLPHub: an e-Infrastructure-based text mining hub
Coro G., Panichi G., Pagano P., Perrone E.
Text mining involves a set of processes that analyze text to extract high-quality information. Among its large number of applications, there are experiments that tackle big data challenges using complex system architectures. However, text mining approaches are neither easy to discover and use nor easily combinable by end-users. Furthermore, they should be contextualized within new approaches to science (eg, Open Science) that ensure longevity and reuse of methods and results. This article presents NLPHub, a distributed system that orchestrates and combines several state-of-the-art text mining services that recognize spatiotemporal events, keywords, and a large set of named entities. NLPHub adopts an Open Science approach, which fosters the reproducibility, repeatability, and reusability of methods and results, by using an e-Infrastructure supporting data-intensive Science.NLPHubaddsOpenScience-compliance to the connected services through the use of representational standards for services and computations. It also manages heterogeneous service access policies and enables collaboration and sharing facilities. This article reports a performance assessment based on an annotated corpus of named entities, which demonstrates that NLPHub can improve the performance of the single-integrated processes by cleverly combining their output.Source: Concurrency and computation (Online) (2020): e5986. doi:10.1002/cpe.5986
DOI: 10.1002/cpe.5986
Project(s): PARTHENOS via OpenAIRE

See at: ISTI Repository Open Access | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | CNR ExploRA Restricted


2020 Journal article Open Access OPEN

Understanding and managing ocean sustainability: the Blue-Cloud project
Candela L., Pasquale P.
The Blue-Cloud flagship project of the Directorate-General (DG) for Research and Innovation Unit of the European Commission is establishing a thematic marine cloud serving the blue economy, marine environment and marine knowledge agendas and the European Open Science Cloud. The project links the horizontal e-infrastructures supported by DG CONNECT and DG GROW, long-term marine data initiatives supported by DG MARE, research infrastructures supported by DG for Research and Innovation and other recently funded thematic clouds.Source: ERCIM news 123 (2020): 11–12.
Project(s): Blue Cloud via OpenAIRE

See at: ercim-news.ercim.eu Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2020 Journal article Open Access OPEN

Realizing virtual research environments for the agri-food community: the AGINFRA PLUS experience
Assante M., Boizet A., Candela L., Castelli D., Cirillo R., Coro G., Fernández E., Filter M., Frosini L., Georgiev T., Kakaletris G., Katsivelis P., Knapen R., Lelii L., Lokers R. M., Mangiacrapa F., Manouselis N., Pagano P., Panichi G., Penev L., Sinibaldi F.
The enhancements in IT solutions and the open science movement are injecting changes in the practices dealing with data collection, collation, processing, analytics, and publishing in all the domains, including agri-food. However, in implementing these changes one of the major issues faced by the agri-food researchers is the fragmentation of the "assets" to be exploited when performing research tasks, for example, data of interest are heterogeneous and scattered across several repositories, the tools modelers rely on are diverse and often make use of limited computing capacity, the publishing practices are various and rarely aim at making available the "whole story" including datasets, processes, and results. This paper presents the AGINFRA PLUS endeavor to overcome these limitations by providing researchers in three designated communities with Virtual Research Environments facilitating the use of the "assets" of interest and promote collaboration.Source: Concurrency and computation (Online) 33 (2020). doi:10.1002/cpe.6087
DOI: 10.1002/cpe.6087
Project(s): AGINFRA PLUS via OpenAIRE

See at: ISTI Repository Open Access | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | CNR ExploRA Restricted | Concurrency and Computation Practice and Experience Restricted


2020 Report Open Access OPEN

Blue Cloud - D4.2: Blue Cloud VRE Common Facilities (Release 1)
Assante M., Candela L., Pagano P., Dell'Amico A., Coro G., Cirillo R., Frosini L., Lelii L., Lettere M., Mangiacrapa F., Panichi G., Sinibaldi F.
The Blue-Cloud project plans to pilot a cyber platform bringing together and providing access to multidisciplinary data from observations and models, analytical tools, and computing facilities essential to support research to understand better and manage the many aspects of ocean sustainability. To achieve this goal, Blue-Cloud is developing, deploying, and operating the Blue-Cloud platform whose architecture consists of two families of components: (a) the Blue Cloud Data Discovery and Access service component to serve federated discovery and access to 'blue data' infrastructures; and (b) the Blue Cloud Virtual Research Environment (VRE) component to provide a Blue Cloud VRE as a federation of computing platforms and analytical services. This deliverable presents the Blue Cloud Virtual Research Environment constituents by focusing on both new services and revised existing services that have been developed in the reporting period to serve the needs of the Blue Cloud community. In particular, this deliverable describes a total of 11 services and components. These services and components contribute functionalities to the Blue Cloud VRE Enabling Framework (Identity and Access Management, VRE Management), Collaborative framework (Workspace and Social Networking), Analytics Framework (Software and Algorithm Importer, Smart Executor), Publishing Framework (Catalogue Service) and improved support for RStudio, JupyterHub, ShinyProxy, and Docker Applications. The services are described below by reporting their design principles, architectures, and main features. The deliverable also describes the procedures and approaches governing services and components released by highlighting how Gitea (as Git hosting service), Jenkins (as automation server), and Maven (as project management and comprehension tool) are used to guarantee continuous integration processes. Services and components discussed in this deliverable contribute to 11 gCube open-source software system releases (from gCube 4.16 up to gCube 4.25.1) and are in the pipeline for the next ones. They have been used to develop and operate the Virtual Laboratories of the Blue Cloud gateway https://blue-cloud.d4science.org and its underlying infrastructure. At the time of this deliverable (November 2020), the gateway hosts a total of 8 VREs and VLabs, including five specifically conceived to support the co-development of some of the Blue-Cloud demonstrators (namely, the Aquaculture Atlas Generation for Demonstrator #5, the Blue-Cloud Lab for several demonstrators, the GRSF pre for Demonstrator #4, the Marine Environmental Indicators for Demonstrator #3, the Zoo-Phytoplankton EOV for Demonstrator #1). This gateway and its tools serve more than 400 users that (since January 2020) performed a total of more than 5000 working sessions, more than 1700 accesses to the Workspace, and more than 750 analytics tasks. These exploitation and uptake indicators are likely to grow in the coming months thanks to data updates and continued use, further development of existing VLabs, and finally, the creation of new ones.Source: Project Report, Blue Cloud, D4.2, 2020
Project(s): Blue Cloud via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2020 Report Open Access OPEN

SoBigData e- Infrastructure Common Facilities 1
Assante M., Bardi A., Fernandez E., Manzi A., Pagano P.
This deliverable reports the design principles and software architectures characterising the release and development of the SoBigData e-Infrastructure common facilities, namely the social mining computational engine, the online coding and workflow design frameworks, and the online science monitoring dashboard. This report is the first of two versions of the document, each of which describing the design associated with a specific version of the infrastructure to be made available at M12 (December 2020) and at the end of the third year (SoBigData e-Infrastructure common facilities 2, December 2022). Specifically, the deliverable focuses on the design principles and reference architectures included in the first release of the SoBigData e-Infrastructure common facilities at M12. The deliverable consists of six sections. Section 1 briefly introduces the role of this deliverable for the development and delivery of the SoBigData e-Infrastructure common facilities. Section 2 describes the SoBigData e-infrastructure logical architecture contextualising the common facilities and how they relate with the rest. Section 3, section 4 and section 5 document the first release of the e-Infrastructure common facilities included in this report and available at M12, reporting the design principles and reference architectures of the released solutions. Specifically, section 3 describes the social mining computational engine, Section 4 presents the online coding and workflow design frameworks - which includes the RStudio and the Jupyter Notebooks via JupyterHub - and Section 5 reports the online science monitoring dashboard. Finally, section 6 concludes the report illustrating the whole Release Management process and its components for continuous integration.Source: Project report, SoBigData, D9.4, 2020
Project(s): SoBigData-PlusPlus via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2020 Report Open Access OPEN

ARIADNEPlus - Initial report on JRA activities
Meghini C., Bardi A., Pagano P., Theodoridou M., Finn J.
This deliverable describes the progress of JRA activities (WP 12-16) carried out during the first year of the ARIADNEplus project, as requested by task 12.6. It offers an integrated overview of all the technological developments of the project in the first 18 months of work, pointing out any delay or relevant issues.Source: Project report, ARIADNEPlus, D12.1, 2020
Project(s): ARIADNEplus via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2020 Report Open Access OPEN

RISIS 2 - Opening of Open Data VRE
Assante M., Baglioni M., Bardi A., Mangiacrapa F., Pagano P.
This report is a short document accompanying the Deliverable "D4.2 Opening of Open Data VRE", which is of type: "Websites, patents filling, etc.". It describes the design of the software components involved in the Open Data VRE, deployed to serve the current needs of the RISIS community.Source: Project report, RISIS 2, D4.2, 2020
Project(s): RISIS 2 via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2020 Report Closed Access

I-GENE - Virtual Research Environment (VRE)
Assante M., Pagano P.
This report documents the D4Science Virtual Research Environment released for the I-GENE Project. Two sections illustrate the activities performed and the characteristics of the I-GENE Virtual Research Environment. Section 2 is the introduction. Section 3, instead, describes the Infrastructure gateway, accessible via the URL https://i-gene.d4science.org/ expected to be the end-user entry point to the I-GENE services, and the I-GENE Project Virtual Research Environment (VRE) and its features, all of which are accessible via the above-described entry point. Section 4 describes the use of VRE for implementing the project scopes. The Science and Technology Institute (ISTI) of the CNR (National Research Council), a third party linked to UNIPI, is responsible for this activity.Source: Project report, I-GENE, D7.2 I, 2020
Project(s): I-GENE via OpenAIRE

See at: CNR ExploRA Restricted


2019 Report Open Access OPEN

SoBigData - D10.10 - Resource adaptation to register to the e-infrastructure 3
Assante M., Candela L., Manghi P., Pagano P.
Deliverable D10.10 "Resource adaptation to register to the e-infrastructure 3" is the revised version of the Deliverable D10.9 "Resource adaptation to register to the e-infrastructure 2" and Deliverable D10.8 "Resource adaptation to register to the e-infrastructure 1" intended to report the experiences of partners from different infrastructures at integrating their services, methods, and applications as SoBigData resources. The first section describes the general integration patterns, while the second section reports the experiences from the individual partners, revealing the effort required, in terms of time and technical complexity, and earned benefits. This revised version of the document covers the whole period of the project, including the up to date information of the D10.9 deliverable and the new experiences of partners at integrating their services, methods, and applications as SoBigData resources, developed through the project's lifetime.Source: Project report, SoBigData, Deliverable D10.10, pp.1–26, 2019
Project(s): SoBigData via OpenAIRE

See at: data.d4science.net Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2019 Report Open Access OPEN

SoBigData - D10.7 - SoBigData e-infrastructure and VRE release
Assante M., Candela L., Cirillo R., Frosini L., Lelii L., Mangiacrapa F., Pagano P.
This deliverable describes the software that has been deployed to serve the needs of the SoBigData community, by delivering the platform and the VREs planned in "D10.4 SoBigData e-Infrastructure release plan 3". In particular, it reports on how such software has been exploited to make available the envisaged components, i.e. the SoBigData portal (and the underlying Virtual Organisation), the SoBigData Catalogue and the SoBigData Virtual Research Environments, together with the list and pointers to the software packages produced by the project and implementing such components, whose operation today constitutes the SoBigData e-infrastructure accessible from http://sobigdata.d4science.org.Source: Project report, SoBigData, Deliverable D10.7, pp.1–28, 2019
Project(s): SoBigData via OpenAIRE

See at: data.d4science.net Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2019 Journal article Open Access OPEN

Reconstructing 3D virtual environments within a collaborative e-infrastructure
Coro G., Palma M., Ellenbroek A., Panichi G., Nair T., Pagano P.
Sets of two dimensional images are insufficient to capture the development in time and space of three-dimensional structures. The 2D 'flattening' of photographs results in a significant loss of features especially if the photos were taken by one person. Automatically collecting and aligning photos in order to render 3D structures from 2D images without specialized equipment, is currently a complex process that requires specialist knowledge with often limited results. In this paper, an Open Science oriented workflow is proposed where an on-line file system is used to share photos of an object or an environment and to produce a virtual reality scene as a navigable 3D reconstruction that can be shared with other people. Our workflow is based on a distributed e-Infrastructure and overcomes common limitations of other approaches by having all the used technology integrated on the same platform and by not requiring specialist knowledge. A performance evaluation of the 3D reconstruction process embedded in the workflow is reported against a commercial software and an open-source software in terms of computational efficiency and reconstruction accuracy, and three marine science use cases are reported to show potential applications of the workflow.Source: Concurrency and Computation: Practice and Experience 31 (2019). doi:10.1002/cpe.5028
DOI: 10.1002/cpe.5028
Project(s): MERCES via OpenAIRE

See at: ISTI Repository Open Access | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | Concurrency and Computation Practice and Experience Restricted | CNR ExploRA Restricted


2019 Journal article Open Access OPEN

The gCube system: delivering virtual research environments as-a-service
Assante M., Candela L., Castelli D., Cirillo R., Coro G., Frosini L., Lelii L., Mangiacrapa F., Marioli V., Pagano P., Panichi G., Perciante C., Sinibaldi F.
Important changes have characterised research and knowledge production in recent decades. These changes are associated with developments in information technologies and infrastructures. The processes characterising research and knowledge production are changing through the digitalization of science, the virtualisation of research communities and networks, the offering of underlying systems and services by infrastructures. This paper gives an overview of gCube, a software system promoting elastic and seamless access to research assets (data, services, computing) across the boundaries of institutions, disciplines and providers to favour collaboration-oriented research tasks. gCube's technology is primarily conceived to enable Hybrid Data Infrastructures facilitating the dynamic definition and operation of Virtual Research Environments. To this end, it offers a comprehensive set of data management commodities on various types of data and a rich array of "mediators" to interface well-established Infrastructures and Information Systems from various domains. Its effectiveness has been proved by operating the D4Science.org infrastructure and serving concrete, multidisciplinary, challenging, and large scale scenarios.Source: Future generation computer systems 95 (2019): 445–453. doi:10.1016/j.future.2018.10.035
DOI: 10.1016/j.future.2018.10.035
Project(s): AGINFRA PLUS via OpenAIRE, BlueBRIDGE via OpenAIRE, ENVRI PLUS via OpenAIRE, EOSCpilot via OpenAIRE

See at: ISTI Repository Open Access | Future Generation Computer Systems Open Access | Future Generation Computer Systems Restricted | Future Generation Computer Systems Restricted | Future Generation Computer Systems Restricted | Future Generation Computer Systems Restricted | CNR ExploRA Restricted | Future Generation Computer Systems Restricted | www.sciencedirect.com Restricted


2019 Contribution to book Open Access OPEN

Methods and tools for supporting the integration of stocks and fisheries
Tzitzikas Y., Marketakis Y., Minadakis N., Mountantonakis M., Candela L., Mangiacrapa F., Pagano P., Perciante C., Castelli D., Taconet M., Gentile A., Gorelli G.
The collation of information for the monitoring of fish stocks and fisheries is a difficult and time-consuming task, as the information is scattered across different databases and is modelled using different formats and semantics. Our purpose is to offer a unified view of the existing stocks and fisheries information harvested from three different database sources (FIRMS, RAM and FishSource), by relying on innovative data integration and manipulation facilities. In this paper, we describe the building blocks in terms of methods and software components that are necessary for integrating stocks and fisheries data from heterogeneous data sources.Source: Information and Communication Technologies in Modern Agricultural Development, edited by Salampasis M., Bournaris T., pp. 20–34, 2019
DOI: 10.1007/978-3-030-12998-9_2
Project(s): BlueBRIDGE via OpenAIRE

See at: link.springer.com Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | link.springer.com Restricted | link.springer.com Restricted


2019 Journal article Open Access OPEN

Enacting open science by D4Science
Assante M., Candela L., Castelli D., Cirillo R., Coro G., Frosini L., Lelii L., Mangiacrapa F., Pagano P., Panichi G., Sinibaldi F.
The open science movement is promising to revolutionise the way science is conducted with the goal to make it more fair, solid and democratic. This revolution is destined to remain just a wish if it is not supported by changes in culture and practices as well as in enabling technologies. This paper describes the D4Science offerings to enact open science-friendly Virtual Research Environments. In particular, the paper describes how complete solutions suitable for realising open science practices can be achieved by integrating a social networking collaborative environment with a shared workspace, an open data analytics platform, and a catalogue enabling to effectively find, access and reuse every research artefact.Source: Future generation computer systems (2019): 555–563. doi:10.1016/j.future.2019.05.063
DOI: 10.1016/j.future.2019.05.063
Project(s): AGINFRA PLUS via OpenAIRE, BlueBRIDGE via OpenAIRE, ENVRI PLUS via OpenAIRE, EOSCpilot via OpenAIRE

See at: ISTI Repository Open Access | Future Generation Computer Systems Restricted | Future Generation Computer Systems Restricted | Future Generation Computer Systems Restricted | Future Generation Computer Systems Restricted | Future Generation Computer Systems Restricted | CNR ExploRA Restricted | Future Generation Computer Systems Restricted


2019 Conference article Open Access OPEN

An Open Science System for Text Mining
Coro G., Panichi G., Pagano P.
Text mining (TM) techniques can extract high-quality information from big data through complex system architectures. However, these techniques are usually difficult to discover, install, and combine. Further, modern approaches to Science (e.g. Open Science) introduce new requirements to guarantee reproducibility, repeatability, and re-usability of methods and results as well as their longevity and sustainability. In this paper, we present a distributed system (NLPHub) that publishes and combines several state-of-the art text mining services for named entities, events, and keywords recognition. NLPHub makes the integrated methods compliant with Open Science requirements and manages heterogeneous access policies to the methods. In the paper, we assess the benefits and the performance of NLPHub on the I-CAB corpus.Source: CLiC-it 2019 Italian Conference on Computational Linguistic, pp. 1–7, Bari, Italy, 13-15/11/2019
Project(s): PARTHENOS via OpenAIRE

See at: disi.unitn.it Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2019 Report Restricted

DESIRA - Deliverable 5.1 - Virtual Research Environment: specification report
Assante M, Cirillo R., Dell'Amico A., Frosini L., Pagano P.
The DESIRA Virtual Research Environment specification consists of a hardware layer and a service layer. The former is made available by the D4Science Infrastructure 1 [1, 2] and it is organized as a dynamic pool of virtual machines, supporting computation and storage. The operations and management of those resources is performed via a set of enabling technologies selected to ensure availability and reliability of the infrastructure while e guaranteeing reduction of costs of ownership and a set of supporting technologies selected to ensure secure monitoring, alerting and provisioning. The service layer, illustrated in Figure 1, consists of three service frameworks, which can be summarized as a follows: o Enabling Framework: the enabling framework, framework , based on the gCube System [3], includes services required to support the operation of all services and the VREs supported by such services. As such it includes: a resource registry service, to which all e-infrastructure infrastructure resources (data sources, services, computational nodes, etc.) can be dynamically (de)registered and discovered by user and other services; Authentication and Authorization services, as well as Accounting Services, capable of both granting ing and tracking access and usage actions from users; and a VRE manager, capable of deploying in the collaborative framework VREs inclusive of a selected number of "applications", generally intended as sets of interacting services; o Storage Framework: the storage framework includes services for efficient, advanced, and on on-demand management of digital data, encoded as: files in a distributed file system, collection of metadata records, and time series in spatial databases; such services are used by all other services in the architecture, exception made for the enabling framework; o Collaborative framework : the collaborative framework includes all services deployed for the scientists and for each of them provides social networking services, user management services, shared workspace services. In addition, addition it comprises the part on the Web UI access to the Virtual Research Environment.Source: Project report, DESIRA, Deliverable D5.1, pp.1–19, 2019

See at: data.d4science.net Restricted | CNR ExploRA Restricted